Medical image coding based on wavelet transform and distributed arithmetic coding

Image compression plays a crucial role in medical imaging, allowing efficient manipulation, storage, and transmission. Nevertheless, in medical applications the need to conserve the diagnostic validity of the image requires the use of lossless compression methods, producing low compression factors. In this paper, a novel near-lossless compression scheme is proposed here and yields significantly better compression rates. In this proposed method, base points, direction images and D-value images are obtained from RGB color space image by transformation. Base points, direction images are encoded by binary coding, distributed arithmetic coding. Wavelet coefficients of D-value images are encoded by adaptive Huffman coding. As a result, high over all compression rates, better diagnostic image quality and improved performance parameters are obtained. The algorithm is tested on experimental medical images from different modalities and different body districts and results are reported.